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Mapping and predicting metabolic fluxes between the ileal microbiome and host

绘制和预测回肠微生物组和宿主之间的代谢通量

基本信息

批准号：
9195132
负责人：
Jason Papin
金额：
$ 34.37万
依托单位：
UNIVERSITY OF VIRGINIA
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-01-15 至 2018-12-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): The relationship between the gut microbiome and human disease is well appreciated but poorly understood. Central to gut microbial community dynamics is how nutrients flow between community members as well as between the community and its host. A presumption exists that nutrient exchange in toto is highly complex and interconnected; as such, functional pathways and circuits remain poorly characterized. The main hypothesis for this proposed program is that nutrient flow between the microbiome and the host is relatively stable despite individual microbiome variation; notwithstanding such stability, there exist central microbial species that drive key metabolic reactions between microbiome and host and that lead to disease when disrupted. With our complementary expertise in metagenomics, metabonomics, computational modeling, and gut microbiome biology, we will address this central hypothesis with the following specific aims: (1) Reconstruct and validate metabolic networks of in vitro synthetic microbial communities directly from meta-transcriptomic sequencing data. We have developed a novel systems biology approach to reconstruct the metabolic networks of individual members of a microbial community directly from meta-transcriptomic data. We will validate this approach with in vitro synthetic microbial communities derived from the altered Schaedler flora; (2) Characterize the in vivo correlation between the ileal microbiome and host metabonome. We will characterize the host (mouse) metabonome (from urine, serum, and ileal lumen) and the ileal microbiome of coupled samples under conditions that alter the microbial community (broad- and narrow-spectrum antibiotics). We will also sequence the meta-transcriptomes of the associated microbiomes. These mappings between the ileal microbiome and host metabonome will be delineated over a longitudinal study with antibiotic-mediated perturbation and subsequent recovery; and (3) Predict and validate stabilizing microbial species within the gut microbiome that account for robustness of the host metabonome and describe corresponding metabolic functionalities. We will predict the keystone species that buffer the metabonome from changes in the microbiome and thus, when disrupted, have the most significant impact on variation in the metabonome. We will characterize the key metabolic pathway niches in the microbiome that enable stability of the host metabonome. We will validate these predictions by selectively killing target species via bacteriophage therapies t manipulate the metabonome as directed by results from the computational modeling and antibiotic-mediated perturbation and recovery studies. The implementation of this proposed program will address fundamental questions in the complex nutrient flow dynamics between host and microbiome. An understanding of the relationship between microbiome composition and host metabolism will be key to the development of probiotic, nutritional, and other therapeutic strategies.

描述（由申请人提供）：肠道微生物组与人类疾病之间的关系得到了很好的理解，但了解甚少。肠道微生物群落动态的核心是营养物质如何在群落成员之间以及群落与宿主之间流动。存在一种假设，即营养交换是高度复杂和相互关联的;因此，功能途径和回路仍然缺乏特征。该计划的主要假设是，尽管微生物组存在个体差异，但微生物组和宿主之间的营养流相对稳定;尽管存在这种稳定性，但存在中心微生物物种，它们驱动微生物组和宿主之间的关键代谢反应，并在中断时导致疾病。凭借我们在宏基因组学，代谢组学，计算建模和肠道微生物组生物学方面的互补专业知识，我们将通过以下具体目标解决这一中心假设：（1）直接从元转录组测序数据重建和验证体外合成微生物群落的代谢网络。我们开发了一种新型系统生物学方法，可以直接从元转录组数据重建微生物群落个体成员的代谢网络。我们将用来自改变的Schaedler植物群的体外合成微生物群落来验证这种方法;（2）表征回肠微生物组和宿主代谢组之间的体内相关性。我们将在改变微生物群落（广谱和窄谱抗生素）的条件下表征宿主（小鼠）代谢物组（来自尿液、血清和回肠腔）和偶联样品的回肠微生物组。我们还将对相关微生物组的元转录组进行测序。回肠微生物组和宿主代谢组之间的这些映射将在具有代谢介导的扰动和随后的恢复的纵向研究中描绘;以及（3）预测和验证肠道微生物组内的稳定微生物物种，其解释宿主代谢组的稳健性并描述相应的代谢功能。我们将预测缓冲代谢组免受微生物组变化的关键物种，因此，当被破坏时，对代谢组的变化产生最显著的影响。我们将描述微生物组中的关键代谢途径小生境，使宿主代谢组稳定。我们将通过噬菌体治疗选择性杀死靶物种来验证这些预测，以根据计算建模和药物介导的扰动和恢复研究的结果来操纵代谢组。该计划的实施将解决宿主和微生物组之间复杂营养流动态的基本问题。了解微生物组组成与宿主代谢之间的关系将是益生菌，营养和其他治疗策略发展的关键。

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Inference of Network Dynamics and Metabolic Interactions in the Gut Microbiome.

DOI：
10.1371/journal.pcbi.1004338
发表时间：
2015-05
期刊：
PLoS computational biology
影响因子：
4.3
作者：
Steinway SN;Biggs MB;Loughran TP Jr;Papin JA;Albert R
通讯作者：
Albert R

PhyloCore: A phylogenetic approach to identifying core taxa in microbial communities.

DOI：
10.1016/j.gene.2016.08.032
发表时间：
2016-11-30
期刊：
Gene
影响因子：
3.5
作者：
Ren T;Wu M
通讯作者：
Wu M

Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA.

DOI：
10.1371/journal.pcbi.1005413
发表时间：
2017-03
期刊：
PLoS computational biology
影响因子：
4.3
作者：
Biggs MB;Papin JA
通讯作者：
Papin JA

Novel co-culture plate enables growth dynamic-based assessment of contact-independent microbial interactions.

新型共培养板能够对不依赖于接触的微生物相互作用进行基于生长动态的评估。

DOI：
10.1371/journal.pone.0182163
发表时间：
2017
期刊：
PloS one
影响因子：
3.7
作者：
MoutinhoJr,ThomasJ;Panagides,JohnC;Biggs,MatthewB;Medlock,GregoryL;Kolling,GlynisL;Papin,JasonA
通讯作者：
Papin,JasonA

Protein- and zinc-deficient diets modulate the murine microbiome and metabolic phenotype.

DOI：
10.3945/ajcn.116.131797
发表时间：
2016-11
期刊：
The American journal of clinical nutrition
影响因子：
0
作者：
Mayneris-Perxachs J;Bolick DT;Leng J;Medlock GL;Kolling GL;Papin JA;Swann JR;Guerrant RL
通讯作者：
Guerrant RL